@inproceedings{castle-moreno-schneider-2025-entity,
    title = "Entity Linking using {LLM}s for Automated Product Carbon Footprint Estimation",
    author = "Castle, Steffen  and
      Moreno Schneider, Julian",
    editor = "Basile, Valerio  and
      Bosco, Cristina  and
      Grasso, Francesca  and
      Ibrohim, Muhammad Okky  and
      Skeppstedt, Maria  and
      Stede, Manfred",
    booktitle = "Proceedings of the 1st Workshop on Ecology, Environment, and Natural Language Processing (NLP4Ecology2025)",
    month = mar,
    year = "2025",
    address = "Tallinn, Estonia",
    publisher = "University of Tartu Library",
    url = "https://preview.aclanthology.org/fix-sig-urls/2025.nlp4ecology-1.12/",
    pages = "56--60",
    ISBN = "978-9908-53-114-4",
    abstract = "Growing concerns about climate change and sustainability are driving manufacturers to take significant steps toward reducing their carbon footprints. For these manufacturers, a first step towards this goal is to identify the environmental impact of the individual components of their products. We propose a system leveraging large language models (LLMs) to automatically map components from manufacturer Bills of Materials (BOMs) to Life Cycle Assessment (LCA) database entries by using LLMs to expand on available component information. Our approach reduces the need for manual data processing, paving the way for more accessible sustainability practices."
}